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danoandco

HN member
Joined
Tue, May 24, 2022, 3:41 PM UTC
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51
Public activity
28 items

About danoandco

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Recent public activity

  1. story
  2. comment
    Comment #47746996

    Definitely and Twill is for SWE delegation first, not so much the “general agent on my machine.”

  3. comment
    Comment #47746987

    It's a crowded market. On the CLI-agnostic cloud agent positioning, there are only startups so far. Only incumbent is Github Agents as you mentioned in another thread.

  4. comment
    Comment #47746935

    Yes, broadly. The main structural difference is that we’re agent-agnostic, so we can combine lab-native CLIs in one workflow. GitHub will likely struggle there because they have di…

  5. comment
    Comment #47727351

    On gh-aw: it looks solid for the event-driven automation shape (triage, docs sync, CI fix). We're after a slightly different shape: interactive back-and-forth, steering from Slack …

  6. comment
    Comment #47726830

    Mmh this works on my end. Sending you an email. Ty

  7. comment
    Comment #47726812

    On computer use: Yes. Sandboxes come with a computer-use CLI for driving Linux GUI apps via X11. On triggers: Cron, GitHub (PRs, issues, @twill mentions in review comments), Slack,…

  8. comment
    Comment #47726457

    Awesome! Thanks for trying it.

  9. comment
    Comment #47724104

    Jules is similar to Twill with the following differences: - Twill is CLI-agnostic, meaning you can use Claude Code, Codex or Gemini. Jules only works with Gemini. - We focus on the…

  10. comment
    Comment #47723766

    On the Twill web app, you can run the same task across different agents and multiple attempts (each in its own sandbox). Then you pick the best result. This is super handy for UI w…

  11. comment
    Comment #47723626

    Similar but reusing lab-native CLIs like Claude Code or Codex, which they perform RL on. And so in the long-run, we believe this approach wins over custom harnesses.

  12. comment
    Comment #47723377

    We’re focused on SWE use cases. Code is nice because there’s already a built-in verification loop: diffs, tests, CI, review, rollback. But you do quickly get to a state where the a…

  13. comment
    Comment #47723158

    Totally right on the compile time. CIs have the same bottleneck, and the ecosystem is working on fixing this (faster cpus, better caching) in both coding agents and CI to improve o…

  14. comment
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    Comment #47722317

    For a solo dev running one task at a time, a beefy desktop overnight is totally viable. We see a lot of this with the Mac Mini hype Cloud starts to matter when you want to (a) run …

  16. comment
    Comment #47722034

    Yes, this is the pass@k metric from code generation research. Found the relevant paper Evaluating Large Language Models Trained on Code (Chen et al., 2021) which introduced the met…

  17. comment
    Comment #47721962

    Claude managed agents is a general-purpose hosted runtime for Claude. While Twill focuses on SWE tasks. And so the SWE workflow is pre-built (research, planning, verification, PR, …

  18. story
    Launch HN: Twill.ai (YC S25) – Delegate to cloud agents, get back PRs

    Hey HN, we're Willy and Dan, co-founders of Twill.ai ( https://twill.ai/ ). Twill runs coding CLIs like Claude Code and Codex in isolated cloud sandboxes. You hand it work through …

  19. story
  20. comment
    Comment #47597110

    Thanks for running it and the feedback! For the ADR vs AGENTS: CLIs usually load the AGENTS.md with a tag saying: "this context may or may not be relevant to your tasks. You should…

  21. story
  22. comment
    Comment #47420001

    true, i think the key thing is explaining somewhere in the repo "why" something was done. like the rationale for choosing X over Y service for instance. maybe this record is just t…

  23. comment
    Comment #47419043

    OpenAI published an article and demo for scoring how well AI agents can work in a codebase ( https://openai.com/index/harness-engineering/ , https://www.youtube.com/watch?v=rhsSqr0…

  24. story
  25. comment
    Comment #44637441

    reminds me of the "memory for agents is a moat" but for software memory for software